Abstract
Rotor blade fault is one of the most causes of turbine failures in turbomachinery. Vibration spectral analysis and blade pass frequency (BPF) monitoring are the most widely used methods for blade faults diagnosis. These methods, were however, have limitations in the detection of incipient faults due to weak and/or transient signals, as well as inability to diagnose the blade faults types. Wavelet analysis has been used as alternative technique to overcome these limitations. However, wavelet analysis itself have some limitations in analyzing signals contains small time alterations and closed frequency components due to lack in its time and frequency resolutions. Most of the studies were conducted in a single stage rotor system rather than multi-stage rotor as most of the gas turbines and compressors used in the industry. Therefore, the objective of this research work is to formulate an effective method for blade fault diagnosis in multi-stage rotor system. In this paper, a novel algorithm was formulated by combining the two newly developed wavelets (High Frequency Resolution (HFR) and High Time Resolution (HTR)). Through signal simulation and experimental studies, the proposed method showed to be effective in detecting types of early/minor blade faults which were otherwise not readily detectable using conventional wavelet and frequency spectrum analysis. The method also showed potential in segregating closely spaced BPFs components and identifying the faulty stage and fault location. The method demonstrated the ability in differentiating various blade faults based on a unique pattern (“fingerprint”) of each fault produced by the newly added wavelet. The formulated algorithm was demonstrated to be suitable in monitoring rotor systems with multiple blade stages.
How to Cite:
Abdelrhman, A., Lee, G., Leong, M., Saam, N., Ahmad, I., Georgantopoulou, C. & Ali, S., (2019) “Early rotor blade fault detection in multi-stage rotor system based on wavelet analysis”, Review of Progress in Quantitative Nondestructive Evaluation .
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